Understanding and predicting customers’ behaviors in customer-centric organizations such as banks are very critical. The aim of identifying customers is to recognize, make distinction, and maintain the high-value customers and to attract more beneficial customers. In the past, the separation of customers into different groups was based on customer requirements, whereas customer value has become more important as segmentation criteria in recent years. Offering cutting-edge banking services, banks’ competition on market share, as well as the psychological and environmental factors of customers’ behavior need to be analyzed over time. Transferring customers to different sectors over time and discovering the dominant models and their displacements between sectors are explored in this paper. We aim to identify the behavioral patterns and the leading characteristics of customer displacements with a focus on the customers of a private bank in Tehran, Iran. For this purpose, we propose a combined method based on clustering and association rules. Results show four dominant clusters of behaviors: "low-value customers with sustainable model", "low-value customer with unsustainable profitability model", "turned away customers with average profitability", "loyal customers with low profitability". We also analyze the relationships between these clusters. The outcomes of this study can play a remarkable role for top managers to take appropriate marketing strategies.